• Asian Journal of Atmospheric Environment
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• v.9 no.4
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• pp.259-271
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• 2015

This study conducted analyses on biogenic volatile organic compounds (BVOC) emission sources contributing to urban ozone ($O_3$) concentration in Osaka Prefecture, Japan in summer 2010 by using the Weather Research and Forecasting model (WRF) version 3.5.1 and the Community Multiscale Air Quality model (CMAQ) version 5.0.1. This prefecture is characterized by highly urbanized area with small forest area. The contributions of source regions surrounding Osaka were estimated by comparing the baseline case and zero-out cases for BVOC emissions from each source region. The zero-out emission runs showed that the BVOC emissions substantially contributed to urban $O_3$ concentration in Osaka (10.3 ppb: 15.9% of mean daily maximum 1-h $O_3$ concentration) with day-by-day variations of contributing source regions, which were qualitatively explained by backward trajectory analyses. Although $O_3$ concentrations were especially high on 23 July and 2 August 2010, the contribution of BVOC on 23 July (35.4 ppb: 25.6% of daily maximum $O_3$) was much larger than that on 2 August (20.9 ppb: 14.2% of daily maximum $O_3$). To investigate this difference, additional zero-out cases for anthropogenic VOC (AVOC) emissions from Osaka and for VOC emissions on the target days were performed. On 23 July, the urban $O_3$ concentration in Osaka was dominantly increased by the transport from the northwestern region outside Osaka with large contribution of $O_3$ that was produced through BVOC reactions by the day before and was retained over the nocturnal boundary layer. On 2 August, the concentration was dominantly increased by the local photochemical production inside Osaka under weak wind condition with the particularly large contribution of AVOC emitted from Osaka on the day.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.307-319
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• 2016

A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

• Journal of Environmental Science International
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• v.21 no.9
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• pp.1097-1113
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• 2012

Ozone is the secondary photochemical pollutant formed from ozone precursor such as nitrogen dioxide and non-methane volatile organic compounds(VOCs). The ambient concentration of ozone depends on several factors: sunshine intensity, atmospheric convection, the height of the thermal inversion layer, concentrations of nitrogen oxides and VOCs. Busan is located in the southeast coastal area of Korea so the ozone concentration of Busan is mainly affected from the meteorological variables related to the sea such as sea breeze. In this study the ozone concentrations of Busan in 2008~2010 were used to analyse the cause of the regional ozone difference in eastern area of Busan. The average ozone concentration of Youngsuri was highest in Busan however the average ozone concentration of Gijang was equal to the average ozone concentration of Busan in 2008~2010. The two sites are located in eastern area of Busan but the distance of two sites is only 9km. To find the reason for the difference of ozone concentration between Youngsuri and Gijang, the meteorological variables in two sites were analyzed. For the analysis of meteorological variables the atmospheric numerical model WRF(Weather Research and Forecasting) was used at the day of the maximum and minimum difference in the ozone concentration at the two sites. As a result of analysis, when the boundary layer height was lower and the sea breeze was weaker in Youngsuri, the ozone concentration of Youngsuri was high. Furthermore when the sea breeze blew from the south in the eastern area of Busan, the sea breeze at Youngsuri turned into the southeast and the intensity of sea breeze was weaker because of the mountain in the southern region of Youngsuri. In that case, the difference of ozone concentration between Youngsuri and Gijang was considerable.

• Atmosphere
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• v.26 no.4
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• pp.617-633
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• 2016

Jangbogo station is located in Terra Nova Bay over the East Antarctica, which is often affected by individual storms moving along nearby storm tracks and a katabatic flow from the continental interior towards the coast. A numerical simulation for two strong wind events of maximum instantaneous wind speed ($41.17m\;s^{-1}$) and daily mean wind speed ($23.92m\;s^{-1}$) at Jangbogo station are conducted using the polar-optimized version of Weather Research and Forecasting model (Polar WRF). Verifying model results from 3 km grid resolution simulation against AWS observation at Jangbogo station, the case of maximum instantaneous wind speed is relatively simulated well with high skill in wind with a bias of $-3.3m\;s^{-1}$ and standard deviation of $5.4m\;s^{-1}$. The case of maximum daily mean wind speed showed comparatively lower accuracy for the simulation of wind speed with a bias of -7.0 m/s and standard deviation of $8.6m\;s^{-1}$. From the analysis, it is revealed that the each case has different origins for strong wind. The highest maximum instantaneous wind case is caused by the approach of the strong synoptic low pressure system moving toward Terra Nova Bay from North and the other daily wind maximum speed case is mainly caused by the katabatic flow from the interiors of Terra Nova Bay towards the coast. Our evaluation suggests that the Polar WRF can be used as a useful dynamic downscaling tool for the simulation and investigation of high wind events at Jangbogo station. However, additional efforts in utilizing the high resolution terrain is required to reduce the simulation error of high wind mainly caused by katabatic flow, which is received a lot of influence of the surrounding terrain.

• Journal of the Korean earth science society
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• v.34 no.3
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• pp.209-223
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• 2013

The purpose of this study was to estimate the contributed concentration of each emission source to $CH_4$ by verifying the simulated concentration of $CH_4$ in the Korean peninsula, and then to compare the $CH_4$ emission used to the $CH_4$ simulation with that of a box model. We simulated the Weather Research Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model to estimate the mean concentration of $CH_4$ during the period of April 1 to 22 August 2010 in the Korean peninsula. The $CH_4$ emissions within the model were adopted by the anthropogenic emission inventory of both the EDGAR of the global emissions and the GHG-CAPSS of the green house gases in Korea, and by the global biogenic emission inventory of the MEGAN. These $CH_4$ emission data were validated by comparing the $CH_4$ modeling data with the concentration data measured at two different location, Ulnungdo and Anmyeondo in Korea. The contributed concentration of $CH_4$ estimated from the domestic emission sources in verification of the $CH_4$ modeling at Ulnungdo was represented in about 20%, which originated from $CH_4$ sources such as stock farm products (8%), energy contribution and industrial processes (6%), wastes (5%), and biogenesis and landuse (1%) in the Korean peninsula. In addition, one that transported from China was about 9%, and the background concentration of $CH_4$ was shown in about 70%. Furthermore, the $CH_4$ emission estimated from a box model was similar to that of the WRF-CMAQ model.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.77-90
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• 2022

Despite the decreasing trend of anthropogenic emissions in East Asia in recent years, haze days still frequently occur in spring. Atmospheric blocking, which occurs frequently in the northeastern Pacific, leads to persistent changes in large-scale circulation and blocks westerly flow in the East Asian region. During March 2019, frequent warm and stagnant synoptic meteorological conditions over East Asia were accompanied 6-7 days later by the Alaskan atmospheric blocking. The Alaskan atmospheric blocking over the period of March 18-24, 2019 led to high particulate matter (PM₁₀) severe haze days exceeding a daily average of 50 ㎍ m^-3 over the period of March 25-28, 2019 in South Korea. Although the high-PM₁₀ severe haze days were caused by warm and stagnant meteorological conditions, the regional contribution of anthropogenic emissions in eastern China was calculated to be 30-40% using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The major regional contributions of PM₁₀ aerosols in the period of high-PM₁₀ severe haze days were as follows: nitrates, 20-25%; sulphates, 10-15%; ammonium, 5-10%; and other inorganics, 15-20%. Ammonium nitrate generated via gas-to-aerosol conversion in a warm and stagnant atmosphere largely contributed to the regional transport of PM₁₀ aerosols in the high-PM₁₀ severe haze days in South Korea.

• Journal of Radiation Protection and Research
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• v.48 no.1
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• pp.28-43
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• 2023

Background: High-fidelity meteorological data is a prerequisite for the realistic simulation of atmospheric dispersion of radioactive materials near nuclear power plants (NPPs). However, many meteorological models frequently overestimate near-surface wind speeds, failing to represent local meteorological conditions near NPPs. This study presents a new high-resolution (approximately 1 km) meteorological downscaling method for modeling short-range (< 100 km) atmospheric dispersion of accidental NPP plumes. Materials and Methods: Six considerations from literature reviews have been suggested for a new dynamic downscaling method. The dynamic downscaling method is developed based on the Weather Research and Forecasting (WRF) model version 3.6.1, applying high-resolution land-use and topography data. In addition, a new subgrid-scale topographic drag parameterization has been implemented for a realistic representation of the atmospheric surface-layer momentum transfer. Finally, a year-long simulation for the Kori and Wolsong NPPs, located in southeastern coastal areas, has been made for 2016 and evaluated against operational surface meteorological measurements and the NPPs' on-site weather stations. Results and Discussion: The new dynamic downscaling method can represent multiscale atmospheric motions from the synoptic to the boundary-layer scales and produce three-dimensional local meteorological fields near the NPPs with a 1.2 km grid resolution. Comparing the year-long simulation against the measurements showed a salient improvement in simulating near-surface wind fields by reducing the root mean square error of approximately 1 m/s. Furthermore, the improved wind field simulation led to a better agreement in the Eulerian estimate of the local atmospheric dispersion. The new subgrid-scale topographic drag parameterization was essential for improved performance, suggesting the importance of the subgrid-scale momentum interactions in the atmospheric surface layer. Conclusion: A new dynamic downscaling method has been developed to produce high-resolution local meteorological fields around the Kori and Wolsong NPPs, which can be used in short-range atmospheric dispersion modeling near the NPPs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.1-10
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• 2010

A regional climate model (RCM) can be a powerful tool to enhance spatial resolution of climate and weather information (IPCC, 2001). In this study we conducted dynamical downscaling using Weather Research and Forecasting Model (WRF) as a RCM in order to obtain high resolution regional agroclimate indices over the Korean Peninsula. For the purpose of obtaining detailed high resolution agroclimate indices, we first reproduced regional weather for the period of March to June, 2002-2008 with dynamic downscaling method under given lateral boundary conditions from NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis data. Normally, numerical model results have shown biases against observational results due to the uncertainties in the modelis initial conditions, physical parameterizations and our physical understanding on nature. Hence in this study, by employing a statistical method, the systematic bias in the modelis results was estimated and corrected for better reproduction of climate on high resolution. As a result of the correction, the systematic bias of the model was properly corrected and the overall spatial patterns in the simulation were well reproduced, resulting in more fine-resolution climatic structures. Based on these results, the fine-resolution agro-climate indices were estimated and presented. Compared with the indices derived from observation, the simulated indices reproduced the major and detailed spatial distributions. Our research shows a possibility to simulate regional climate on high resolution and agro-climate indices by using a proper downscaling method with a dynamical weather forecast model and a statistical correction method to minimize the model bias.

• Atmosphere
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• v.18 no.4
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• pp.339-354
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• 2008

A numerical simulation of a heavy snowfall event that occurred 13 January 2008 along the Yeongdong coastal area, was performed using WRF (Weather Research and Forecasting) in order to reveal mesoscale structures and to construct a conceptual model showing the meteorological background that caused the large difference in snowfall amounts between the Yeongdong mountain area and the Yeongdong coastal area. The simulation results matched well with various observations such as corresponding 12h-accumulated observed precipitation, surface wind obscrvation, radar echoes, and satellite infrared images. The simulation and the observations showed that the scale of the event was of meso - $\beta$ and meso - $\gamma$ scale. The simulation represented well the mesoscale process causing the large difference in snowfall amounts in the two areas. First, wind flow was kept, to a certain extent, from crossing the mountains due to the blocking effect of the low Froude number (~1). The northeast flow over the adjaccnt sea tumcd northwest as it approachcd the mountains, where it was trapped, allowing so-called cold air damming. Second, a strong convergence area formed where the cold northwest flow along the Yeongdong coastal area and the relatively warm and moist northeast flow advecting toward the coast met, supporting the fonllation of a coastal front. Thus, the vertical motion was strongest over the front located near the coast, leading to the heavy snowfall there rather than in the remote mountain area.

• Journal of Environmental Science International
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• v.19 no.6
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• pp.689-701
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• 2010

The effects of high-resolution wind profiler (HWP) data on the wind distributions were evaluated in two different coastal areas during the study period (23-26 August, 2007), indicating weak-gradient flows. The analysis was performed using the Weather Research and Forecasting (WRF) model coupled with a three-dimensional variational (3DVAR) data assimilation system. For the comparison purpose, two coastal regions were selected as: a southwestern coastal (SWC) region characterized by a complex shoreline and a eastern coastal (EC) region surrounding a simple coastline and high mountains. The influence of data assimilation using the HWP data on the wind distributions in the SWC region was moderately higher than that of the EC region. In comparison between the wind speed and direction in the two coastal areas, the application of the HWP data contributed to improvement of the wind direction distribution in the SWC region and the wind strength in the EC region, respectively. This study suggests that the application of the HWP data exerts a large impact on the change in wind distributions over the sea and thus can contribute to the solution to lack of satellite and buoy data with their observational uncertainty.